Otomoto
Feature Importances
Regression Stats
Individual Predictions
What if...
Feature Dependence
Decision Trees
Feature Importances
Model Summary
metric
Score
mean-squared-error
353588671.939
root-mean-squared-error
18803.954
mean-absolute-error
5319.781
mean-absolute-percentage-error
0.037
R-squared
0.981
Predicted vs Actual
Residuals
Plot vs feature
Are predictions and residuals correlated with features?
Individual Predictions
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Prediction
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Contributions Plot
How has each feature contributed to the prediction?
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Partial Dependence Plot
Contributions Table
How has each feature contributed to the prediction?
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What if...
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Prediction
input data incorrect
Feature Input
Adjust the feature values to change the prediction
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1
26
24
25
3
8
7
13
20
34
32
28
29
9
12
6
16
19
33
5
18
30
11
23
14
17
21
0
22
4
31
27
10
2
15
Contributions Plot
How has each feature contributed to the prediction?
input data incorrect
Partial Dependence Plot
input data incorrect
Contributions Table
How has each feature contributed to the prediction?
input data incorrect
Feature Dependence
Shap Summary
Ordering features by shap value
Shap Dependence
Relationship between feature value and SHAP value
Decision Trees
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Decision Trees
Displaying individual decision trees inside xgboost model
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Decision path table
Decision path through decision tree
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